11 of 11 Remote/Hybrid Anomaly Detection Jobs in the North of England

toxic combinations, identity exposure, control gaps, and vulnerability prioritization. Build and evaluate graph algorithms and ML models including centrality, community detection, similarity, anomaly detection, node classification, link prediction, embeddings, and Graph Neural Networks. Design GraphRAG and knowledge-grounded security assistants that combine graph traversal, vector … JanusGraph . Graph data science: Neo4j Graph Data Science, NetworkX , PyTorch Geometric or DGL; graph embeddings, pathfinding, similarity, clustering, link prediction, node classification, anomaly detection, and GNN development. Programming and engineering: Advanced Python and SQL; APIs; test automation; data structures; distributed processing; Git; CI/CD; containers ...

should expect to join customers periodically and for technical discussions. Engineers who never meet the customer build the wrong thing. KEY RESPONSIBILITIES Take our anomaly detection work from proof of concept into production across the estate, moving from retrospective analysis to live early warning. Build the validation … stack. Hands‐on experience with time‐series, sensor or telemetry data at scale, including the realities of gaps, drift, flatlines and misbehaving devices. Applied anomaly detection or predictive modelling taken into production, with the judgement to keep methods robust and explainable rather than elaborate. Practical experience building ...

libraries such as scikit-learn, TensorFlow, or PyTorch. Practical knowledge of algorithms and techniques such as regression, decision trees, random forest, XGBoost, k-means, anomaly detection, and time series forecasting. Working understanding of model evaluation and explainability concepts, e.g. overfitting, bias, cross-validation. Experience developing and implementing ...

platforms and AI workloads using metrics, logs, traces and telemetry. Establish operational insight models that support proactive decision-making and enable advanced capabilities including anomaly detection, event intelligence, noise reduction and predictive operational analytics.• AI Operations & Service Reliability: Apply reliability engineering principles to AI-enabled services, monitoring ...

vaulting, and distributed secrets via external‐secrets patterns (e.g., AWS Secrets Manager, Azure Key Vault). Apply AI‐assisted tooling and analytics to improve anomaly detection, provisioning accuracy, and audit evidence of quality, while maintaining governance and data‐protection standards. Collaborate with engineering, operations, compliance, and security ...

applied within service management to improve operational efficiency, employee experience and service outcomes.* Awareness of modern AIOps and observability capabilities, including monitoring, event correlation, anomaly detection, intelligent alerting, operational analytics and automation.* Familiarity with enterprise service management platforms such as ServiceNow, Jira Service Management, Freshworks or similar ...

perfectly defined requirements. Experience with time-series techniques such as ARIMA, exponential smoothing or related forecasting methods. Experience developing customer churn, lifetime value, propensity, anomaly-detection or segmentation models. Experience analysing financial, operational, customer or risk data. Experience using machine-learning techniques beyond traditional statistical analysis. Experience ...

perfectly defined requirements. Experience with time-series techniques such as ARIMA, exponential smoothing or related forecasting methods. Experience developing customer churn, lifetime value, propensity, anomaly-detection or segmentation models. Experience analysing financial, operational, customer or risk data. Experience using machine-learning techniques beyond traditional statistical analysis. Experience ...

perfectly defined requirements. Experience with time-series techniques such as ARIMA, exponential smoothing or related forecasting methods. Experience developing customer churn, lifetime value, propensity, anomaly-detection or segmentation models. Experience analysing financial, operational, customer or risk data. Experience using machine-learning techniques beyond traditional statistical analysis. Experience ...

Site Reliability Engineering (SRE) maturity, embedding monitoring, observability, automated testing and structured incident response Drive adoption of automation and AI‐enabled tooling to improve anomaly detection, incident management, vulnerability management and operational efficiency Provide technical oversight of production operations, ensuring alignment between platform standards and operational support ...

experience with R and/or Python Solid understanding of core methods: classification, regression, forecasting, clustering, nearest neighbour, neural networks, embeddings, dimensionality reduction and anomaly detection Strong statistical knowledge and the ability to translate complex findings for non‐technical audiences Experience delivering end‐to‐end data science ...